Digital force prediction for milling

Journal Article · 23 June 2020 · Procedia Manufacturing

DOI: https://doi.org/10.1016/j.promfg.2020.05.125 · OSTI ID:1649315

Gomez, Michael ^[1]; No, Timothy ^[2]; Schmitz, Tony ^[1]

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1. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Univ. of Tennessee, Knoxville, TN (United States)
2. Univ. of Tennessee, Knoxville, TN (United States)

This paper presents a fully digital, integrated approach for milling force prediction with arbitrary end mill-work material combinations. The approach includes: 1) structured light scanning to identify the end mill’s cutting edge macro-geometry along the tool axis; 2) structured light scanning to measure the cutting edge cross-sectional rake and relief profiles; 3) finite element analysis of orthogonal cutting to determine the force model coefficients that relate the force to chip area using the work material’s constitutive model and tool’s rake and relief profiles; and 4) time domain simulation with inputs that include the measured cutting edge macro-geometry, finite element-based force model, and measured structural dynamics. Milling force predictions are compared to in-process measurements to validate the method.

• Research Organization: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
• Sponsoring Organization: USDOE Office of Energy Efficiency and Renewable Energy (EERE)
• Grant/Contract Number: AC05-00OR22725
• OSTI ID: 1649315
• Journal Information: Procedia Manufacturing, Vol. 48, Issue 1; ISSN 2351-9789
• Publisher: ElsevierCopyright Statement
• Country of Publication: United States
• Language: English